SP1 Subpixel Optimization Support

The SP1 is now able to provide subpixel accurate disparity
maps. Its accuracy has been increased to 1/16 pixel while
maintaining the same stereo matching efficiency.

We have finally finished work on subpixel optimization for the SP1 stereo
vision sensor. In our previous development prototype, the SP1 produced disparity
maps with integer accuracy. The coarse granularity of an integer disparity
map can cause visible artifacts when observing slanted surfaces. This effect
can be well observed in our previous product video.
A frame from this video where the effect is particularly visible is shown
in Figure 1.

Figure 1: Previous method without subpixel optimization.

In order to remove these artifacts it is necessary to improve the measurement accuracy.
Particularly, we have to measure disparities at resolutions well below one pixel. This can
be achieved by using subpixel optimization techniques, which are usually applied after an
initial run of a stereo matching algorithm.

We have successfully implemented a subpixel optimization method in the SP1 stereo
vision sensor. This allows us to measure disparities at resolutions of only 1/16 pixel.
When we re-process the previous example with this new method, we receive the results
shown in Figure 2. As we can see, the surface now appears perfectly smooth with no
visible artifacts.

Figure 2: New method with subpixel optimization.

Even with subpixel optimization, the SP1 does not lose any of its efficiency.
It is still capable of delivering full-resolution disparity maps at a rate of 30 Hz.
We have updated the SP1 product page
with the new technical details.